Introducing Adaptive Incremental Dynamic Analysis: A New Tool for Linking Ground Motion Selection and Structural Response Assessment

Adaptive Incremental Dynamic Analysis (AIDA) is a novel ground motion selection scheme that adaptively changes the ground motion suites at different ground motion intensity levels to match hazardconsistent properties for structural response assessment. Incremental DynamicAnalysis (IDA), a current dynamic response history analysis practice in Performance-Based Earthquake Engineering (PBEE), uses the same suite of ground motions at all Intensity Measure (IM) levels to estimate structural response. Probabilistic Seismic Hazard Analysis (PSHA) deaggregation tells us, however, that the target distributions of important ground motion properties change as the IM levels change. To match hazard-consistent ground motion properties, ground motions can be re-selected at each IM level, but ground motion continuity is lost when using such “stripes” (i.e., individual analysis points at each IM level). Alternatively, the data from the same ground motions in IDA can be re-weighted at various IM levels to match their respective target distributions of properties, but this implies potential omission of data and curse of dimensionality. Adaptive Incremental Dynamic Analysis, in contrast, gradually changes ground motion records to match ground motion properties as the IM level changes, while also partially maintaining ground motion continuity without the omission of useful data. AIDA requires careful record selection across IM levels. Potential record selection criteria include ground motion properties from deaggregation, or target spectrum such as the Conditional Spectrum. Steps to perform AIDA are listed as follows: (1) obtain target ground motion properties for each IM level; (2) determine “bin sizes” (i.e., tolerance for acceptable ground motion properties) and identify all candidate ground motions that fall within target bins; (3) keep ground motions that are usable at multiple IM levels, to maintain continuity; (4) use each ground motion for IDA within its allowable IM range. As a result, if we keep increasing the “bin sizes”, AIDA will approach IDA asymptotically; on the other hand, if we decrease the “bin sizes”, AIDA will approach the other end of “stripes”. This paper addresses the challenges of changing records across various IM levels. Different ground motion selection schemes are compared with AIDA to demonstrate the advantages of using AIDA. Example structural analyses are used to illustrate the impact of AIDA on the estimation of structural response in PBEE. By combining the benefits of IDA and PSHA without the omission of useful data, AIDA is a promising new tool for linking ground motion selection and structural response assessment

Probabilistic Sea-Level Rise Hazard Analysis

This paper proposes a framework termed Probabilistic Sea-Level Rise Hazard Analysis (PSLRHA), to integrate the sea-level rise knowledge of current climate change scientific communities for informed engineering and policy decisions that affect coastal infrastructure, populations, and ecosystems. PSLRHA combines probabilities of all emission scenarios with predictions of the resulting sea-level rise over time, in order to compute sea-level rise hazard. PSLRHA also incorporates uncertainties in those sea-level rise predictions, by considering multiple Sea-Level Rise Prediction Models (SLRPMs). The output of the PSLRHA framework could be a Global Sea-Level Rise Hazard Map (GSLRHM) that can be used for Performance- Based Sea-Level Rise Engineering (PBSLRE)

Conditional Spectrum Computation Incorporating Multiple Causal Earthquakes and Ground‐Motion Prediction Models

The Conditional Spectrum (CS) is a target spectrum (with conditional mean and conditional standard deviation) that links seismic hazard information with ground motion selection for nonlinear dynamic analysis. Probabilistic seismic hazard analysis (PSHA) estimates the ground motion hazard by incorporating the aleatory uncertainties in all earthquake scenarios and resulting ground motions as well as the epistemic uncertainties in ground motion prediction models (GMPMs) and seismic source models. Typical CS calculations to date are produced for a single earthquake scenario using a single GMPM, but more precise use requires consideration of at least multiple causal earthquakes and multiple GMPMs that are often considered in a PSHA computation. This paper presents the mathematics underlying these more precise CS calculations. Despite requiring more effort to compute than approximate calculations using a single causal earthquake and GMPM, the proposed approach produces an exact output that has a theoretical basis. To demonstrate the results of this approach and compare the exact and approximate calculations, several example calculations are performed for real sites in the western U.S. (WUS). The results also provide some insights regarding the circumstances under which approximate results are likely to closely match more exact results. To facilitate these more precise calculations for real applications, the exact CS calculations can now be performed for real sites in the U.S. using new deaggregation features in the U.S. Geological Survey hazard mapping tools. Details regarding this implementation are discussed in this paper

Conditional Spectrum-Based Ground Motion Selection. Part I: Hazard Consistency for Risk-Based Assessments

The conditional spectrum (CS, with mean and variability) is a target response spectrum that links nonlinear dynamic analysis back to probabilistic seismic hazard analysis for ground motion selection. The CS is computed on the basis of a specified conditioning period, whereas structures under consideration may be sensitive to response spectral amplitudes at multiple periods of excitation. Questions remain regarding the appropriate choice of conditioning period when utilizing the CS as the target spectrum. This paper focuses on risk-based assessments, which estimate the annual rate of exceeding a specified structural response amplitude. Seismic hazard analysis, ground motion selection, and nonlinear dynamic analysis are performed, using the conditional spectra with varying conditioning periods, to assess the performance of a 20-story reinforced concrete frame structure. It is shown here that risk-based assessments are relatively insensitive to the choice of conditioning period when the ground motions are carefully selected to ensure hazard consistency. This observed insensitivity to the conditioning period comes from the fact that, when CS-based ground motion selection is used, the distributions of response spectra of the selected ground motions are consistent with the site ground motion hazard curves at all relevant periods; this consistency with the site hazard curves is independent of the conditioning period. The importance of an exact CS (which incorporates multiple causal earthquakes and ground motion prediction models) to achieve the appropriate spectral variability at periods away from the conditioning period is also highlighted. The findings of this paper are expected theoretically but have not been empirically demonstrated previously

The Inhalation Characteristics of Patients When They Use Different Dry Powder Inhalers

Background: The characteristics of each inhalation maneuver when patients use dry powder inhalers (DPIs) are important, because they control the quality of the emitted dose. Methods: We have measured the inhalation profiles of asthmatic children [CHILD; n=16, mean forced expiratory volume in 1 sec (FEV1) 79% predicted], asthmatic adults (ADULT; n=53, mean predicted FEV1 72%), and chronic obstructive pulmonary disease (COPD; n=29, mean predicted FEV1 42%) patients when they inhaled through an Aerolizer, Diskus, Turbuhaler, and Easyhaler using their “real-life” DPI inhalation technique. These are low-, medium-, medium/high-, and high-resistance DPIs, respectively. The inhalation flow against time was recorded to provide the peak inhalation flow (PIF; in L/min), the maximum pressure change (ΔP; in kPa), acceleration rates (ACCEL; in kPa/sec), time to maximum inhalation, the length of each inhalation (in sec), and the inhalation volume (IV; in liters) of each inhalation maneuver. Results: PIF, ΔP, and ACCEL values were consistent with the order of the inhaler's resistance. For each device, the inhalation characteristics were in the order ADULT>COPD>CHILD for PIF, ΔP, and ACCEL (p4 L and ΔP >4 kPa. Conclusion: The large variability of these inhalation characteristics and their range highlights that if inhalation profiles were used with compendial in vitro dose emission measurements, then the results would provide useful information about the dose patients inhale during routine use. The inhalation characteristics highlight that adults with asthma have greater inspiratory capacity than patients with COPD, whereas children with asthma have the lowest. The significance of the inhaled volume to empty doses from each device requires investigation

Map Resources – ECO Farms in the Czech Republic

The present paper deals with the creation of maps for the sake of a special map portal using the database of eco farms in the Czech Republic. The map output is being developed and implemented within the framework of the Research Program in mutual cooperation of the Department of Information Technologies, Information and Consulting Centre, other departments of the Faculty of Economics and Management CULS Prague with external partners, especially with the Ministry of Agriculture (Environment and Ecological Agriculture Section, Department of Ecological Agriculture) and the Institute of Agricultural Economics and Information (UZEI) - Division of Agro-environmental Policy in Brno. The maps are visualized by means of MPPR 1.0 system and have been processed – in the pilot stage - for the South Bohemian Region eco farms. The results represent initial data from 2009 (as at 31st December 2009) that have been processed, verified and complemented in the course of 2010

Inhalable fucoidan microparticles combining two antitubercular drugs with potential application in pulmonary tuberculosis therapy

The pulmonary delivery of antitubercular drugs is a promising approach to treat lung tuberculosis. This strategy not only allows targeting the infected organ instantly, it can also reduce the systemic adverse effects of the antibiotics. In light of that, this work aimed at producing fucoidan-based inhalable microparticles that are able to associate a combination of two first-line antitubercular drugs in a single formulation. Fucoidan is a polysaccharide composed of chemical units that have been reported to be specifically recognised by alveolar macrophages (the hosts of Mycobacterium). Inhalable fucoidan microparticles were successfully produced, effectively associating isoniazid (97%) and rifabutin (95%) simultaneously. Furthermore, the produced microparticles presented adequate aerodynamic properties for pulmonary delivery with potential to reach the respiratory zone, with a mass median aerodynamic diameter (MMAD) between 3.6-3.9 mu m. The formulation evidenced no cytotoxic effects on lung epithelial cells (A549), although mild toxicity was observed on macrophage-differentiated THP-1 cells at the highest tested concentration (1 mg/mL). Fucoidan microparticles also exhibited a propensity to be captured by macrophages in a dose-dependent manner, as well as an ability to activate the target cells. Furthermore, drug-loaded microparticles effectively inhibited mycobacterial growth in vitro. Thus, the produced fucoidan microparticles are considered to hold potential as pulmonary delivery systems for the treatment of tuberculosis.Portuguese Foundation for Science and Technology [PTDC/DTP-FTO/0094/2012, UID/Multi/04326/2013, UID/BIM/04773/2013]; CAPES-Brazil [BEX 1168/13-4